GVU Technical Report Number:
GIT-GVU-99-41
Title:
Automatic Joint Parameter Estimation from Magnetic Motion Capture Data
Authors:
James F. O'Brien
Bobby Bodenheimer
Gabriel J. Brostow
Jessica K. Hodgins
Abstract:
This paper describes a technique for using magnetic motion capture data to
determine the joint parameters of an articulated hierarchy. This
technique makes it possible to determine the limb lengths, joint locations,
and sensor placement for a human subject without external measurements.
Instead, the joint parameters are inferred with high accuracy from the
motion data acquired during the capture session. The parameters are
computed by performing a linear least squares fit of a revolute joint
model to the input data. A hierarchical structure can also be determined in
situations where the topology of the articulated model is not known. We
present the results of running the algorithm on human motion capture data,
as well as validation results obtained with data from a simulation and
a wooden linkage of known dimensions.
Keywords:
Animation, motion capture, kinematics, parameter estimation, joint
locations, articulated figure, articulated hierarchy
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